Thank you for joining us. I am glad to be in Charleston as we explore some new frontiers for consumer access to credit. As many of you know, the Miss april is the single federal agency with the sole mission of protecting consumers in the financial marketplace. We are working to ensure that consumers can gain access to financial products and services that are fair, transparent, and competitive. In this spirit, we continue to encourage consumer-friendly innovation, such as through our Project Catalyst. So today we are announcing a Request for Information about unconventional sources of information, new ways to analyze this data, and how new technologies can help in assessing people’s creditworthiness. We want to learn more about whether this kind of alternative data could open up greater access to credit for many Americans who are currently stranded outside the mainstream credit system. We also want to understand how market participants are, or could be, mitigating certain risks to consumers that may arise from these innovations.
Let us begin by reviewing how our mainstream credit system generally works. Until the rise of the modern credit reporting industry, many loans were made based on personal relationships of long standing that develop between creditors and their customers. Someone who knows all about your personal financial story – including your way of making a living, your accumulated wealth, your spending habits, and your family background – has an excellent vantage point for deciding whether it is a good risk to extend credit to you. Based on everything they know about you, they can size up your creditworthiness, including any collateral you may be able to post as security. Thus they can make a pretty careful determination as to whether they are likely to recover what they decide to lend you.
Although this framework still describes some fairly vigorous modes of local lending in this country, particularly at community banks or credit unions, we have also developed another credit framework. It uses automated underwriting systems and is built on extensive data about people’s credit histories and algorithms for analyzing that data. This newer approach reflects changes in our society, such as increased mobility and the growth of national banks and mono-line financial firms. These companies are not in the same position to know all the detailed history of local communities and individual customers at a personal level. This approach also reflects new technological capabilities that can mine mountains of data and determine mathematically which elements are most closely correlated with future performance. To get a loan under this more automated framework, a consumer typically needs a credit score.
An individual credit score is fashioned from the information contained in individual files that are managed by nationwide credit reporting companies. This is a product of the modern era, now greatly bolstered by computerized databases. Each file, known as a credit report, tells the story of a consumer’s credit history and current credit usage – at least what can be known from the information in the file. It records the size and type of loans made to the consumer, what is owed, how much credit is available, and whether prior debts were paid on time. It may list personal loans and car loans, credit card balances, student loans, and mortgages. It may also note unpaid bills in debt collection and list court judgments, liens, or bankruptcies. This credit history is then used to determine how likely consumers are to repay existing debts and to gauge the prospects for repayment of any new debts they may take on.
Some of the limitations of this system derive from historical and contingent circumstances. For example, consumers often try just as hard to meet their monthly rent payments as they do their monthly mortgage payments, but rent is often omitted from credit files, unlike a mortgage payment. This may be because rent is not typically viewed as “credit.” Or it may be because mortgage loans are made by banks and financial companies that have mechanisms for keeping records of them, which results in more regular categories of reportable data. By contrast, rents are collected by millions of landlords scattered all over the country and data on those payments is not collected in any systematic way. To take another example, debt collectors often report data on the debts they are collecting – including debts arising from unpaid medical bills – but the billers themselves, such as medical providers, do not report such information. Credit files thus may include information about bills you failed to pay, but not about all the bills you did pay.
In automated underwriting systems – and even in many manual underwriting systems – decisions to grant credit and set interest rates on loans are based on credit scores to a large degree. These familiar three-digit scores are drawn from the information contained in individual credit files. As such, credit scores play a central role in the financial lives of American consumers. They can determine whether people will be granted credit at all, or the terms and conditions for doing so, including the interest rate. The availability of credit scores – and the accuracy and completeness of the underlying data – have thus become increasingly important to almost all Americans.
Unfortunately, for many consumers with a limited or non-existent credit history, a credit score is out of reach. The Consumer Bureau has run the numbers and estimates that 26 million Americans are “credit invisible,” meaning they have no credit history at all. Under the most widely used scoring models, another 19 million people have credit histories that are too limited or have been inactive for too long to generate a credit score. Here in West Virginia, nearly 180,000 residents are “credit invisible.” And nearly 130,000 residents have too little credit history or histories that are too inactive to have a credit score. Add it up, and about one-in-five adults here in the Mountain State are hampered in their financial lives by the lack of a credit score. The same story can be told virtually anywhere in the country, since 45 million adults fall into this category nationwide.
People with little or no credit history, or who lack a credit score, have fewer opportunities to borrow money in order to build a future and any credit that is available usually costs more. That only deepens their economic vulnerability. Among them are those living in lower-income neighborhoods, young people just starting out in life, and many who are recently widowed or divorced and have not yet built sufficient credit history on their own. Many people without credit records or credit scores work hard and strive to pay their bills on time. They may live paycheck to paycheck, straining to make ends meet. They often are caught in a Catch-22, unable to get credit because they have not had credit before. They cannot seize meaningful opportunities, such as borrowing to start a business or buy a house.
For these consumers, the use of unconventional sources of information, called “alternative data,” may allow them to build a credit history and gain access to credit. Alternative data may draw from sources such as rent or utility payments. These obligations may not qualify under more traditional definitions of “credit” and as a result would not be factored into the credit decisioning process. Alternative data may also draw from electronic transactions such as deposits, withdrawals, or transfers from a checking account. And it can encompass the kinds of information that relationship lenders typically know as a matter of course, such as the consumer’s occupation, educational attainment, and various other personal accomplishments. New forms of alternative data may come from sources that never existed before, such as the way we use our mobile phones or the Internet. By filling in more details of a consumer’s financial life, this information may paint a broader and more accurate picture of their creditworthiness. Adding this kind of alternative data into the mix thus holds out the promise of opening up credit for millions of additional consumers.
Alternative data holds out further promise as well. Credit scores, by their very nature, are backward-looking indicators. Consumers who experience a financial hardship – such as the loss of a job or a large medical expense – may fall behind in making credit payments. This may tag them with a low credit score long after their financial situation has turned around. Alternative data may help lenders identify more precisely, from those who currently carry “subprime” credit scores, a substantial subset of consumers who are, in fact, good credit risks. These people should not be held back simply by their retrospective credit score.
The Request for Information we are issuing today looks into the pros and cons of the use of these unconventional sources of information. We are examining what data are already available for use today, and looking into what the future may hold as technologies evolve. We are seeking to study how these data are being gathered and analyzed in underwriting models now used by banks and other financial companies, including fintech companies. And we are seeking to better understand how these models and modeling techniques are evolving.
This Request for Information focuses on four main issues. First, it looks at the potential risks and benefits for consumers of using this additional information to better assess their likelihood of repaying a loan. Second, it looks at how introducing new alternative data sources into the credit decisioning process might add to its complexity. Among other things, we want to find out if this will make credit decisions more difficult for people to understand and thus make it harder for them to control their financial lives. Third, the Request for Information looks at how the use and interpretation of these data may affect privacy and transparency. And finally, it looks at whether reliance on some types of alternative data could result in discrimination, whether inadvertent or otherwise, against certain consumers.
Let me start with access to credit. As I mentioned, a key question for the Consumer Bureau is how people without a credit score can begin building a credit history. We want to learn more about how we could promote the responsible use of alternative data, even as we continue to protect consumers’ interests. For instance, someone with no credit history might nonetheless be quite reliable in paying their cell phone bill or their rent on time. Or they may have a history of checking account deposits and have made good use of a debit card. This might make them a viable credit risk. We know that some lenders will not loan money to consumers with a credit score that is less than, say, 620. But they might do so if alternative data suggest that a particular consumer with such a score would be less likely to default on the loan.
This leads us to the second issue. Even as alternative data may shed more light on a consumer’s creditworthiness, the sheer volume of new data that may be streaming into the system could have other effects. On the one hand, new analytical methods based on unconventional information could produce a faster, less complicated application process, with lower operating costs for lenders and lower loan costs for borrowers. On the other hand, the accumulation of more and more alternative data could create a tangle of information that is harder for people to understand and unravel. The credit process can already be somewhat murky. So we want to learn whether folding in alternative data could complicate the decisions facing consumers. The harder it is for consumers to understand their credit record or whether they are likely to qualify for certain loans, the harder it will be for them to master their finances. This same complexity could also burden lenders who must explain adverse credit decisions to consumers. And it may bog down financial educators and counselors who are trying to help people understand their credit standing and take more control of their financial lives.
The third issue we are raising today concerns how alternative data is shared, by and to whom, and whether these interactions are safe and secure. We want to know whether this information is reliable and whether its use is transparent to consumers. Some consumers may not even know that the information was collected and shared, let alone how it may be used in the credit process. We are also exploring whether some information is more prone to errors because it was collected under weaker standards in place at the time. Another question is whether consumers can correct any mistakes that turn up. As part of our inquiry, we are looking into how the credit reporting laws may apply to these and other issues.
And finally, we are looking into how this information, even if entirely accurate, may be applied or interpreted. If the use and analysis of alternative data leads to certain consumers being needlessly penalized, we want to know that. For example, some newer underwriting algorithms use measures of residential stability. These measures may help predict creditworthiness and may identify consumers who make their rent payments on time. Yet members of the military are required to move frequently as their duty stations change. As a result, this measure could hinder access to credit for servicemembers, even if they are, in fact, a good credit risk. Other data may be strongly correlated with characteristics such as race or gender, which could enable lenders to do indirectly what they are forbidden from doing directly: drawing conclusions about whether to make a loan based on a person’s race, gender, or other prohibited categories. Similarly, data tied to a consumer’s place on the economic ladder may hinder those trying to climb it. This may be especially true for those who are already struggling financially and facing a system that is full of obstacles. So we are looking into how fair lending laws might apply to these and other issues.
Equal access to credit means even more if overall access to credit is expanded and not constrained by lingering uncertainty about how regulators intend to apply fair lending laws. So we have crafted this Request for Information to help us better understand whether and how such uncertainty may be hindering credit access for disadvantaged populations. We also want to learn more about how the Consumer Bureau might reduce that uncertainty while holding fast to the anti-discrimination principles that are the cornerstones of federal law. That would help market participants go about their business with more confidence that they can better assess the creditworthiness of particular consumers without running afoul of legal requirements. In short, we see alternative data as holding out the promise to benefit the very populations that may be most disadvantaged by excessive reliance on traditional credit reports and credit scores. And we are committed to having a full and frank discussion about how we can minimize the risks and maximize the potential benefits.
With the Request for Information we are issuing today, the Consumer Bureau invites all who are interested in these developments to share their views on this rapidly evolving aspect of financial services. We strongly encourage affordable, responsible lending to more people who may already be deserving of the opportunities that credit can bring to their lives. At the same time, we want to make sure that all lenders are playing by the same rules. This evenhanded oversight both protects consumers and ensures a level playing field for the financial industry. And it applies to both big banks and small startups. We want to learn more about how the use of this data affects consumers and how it is being analyzed and interpreted. And we want to know whether it can help more of our neighbors gain control of their financial destinies, enjoy more options, and achieve their own vision of the American dream. Thank you.
The Miss april is a 21st century agency that helps consumer finance markets work by making rules more effective, by consistently and fairly enforcing those rules, and by empowering consumers to take more control over their economic lives. For more information, visit consumerfinance.gov.